Nature Physics

Microtubules (MTs) and their motor proteins collectively harness chemical energy to generate mechanical work, driving some of the most coordinated self-organized dynamics in living cells. The unique properties of these molecules also make them versatile building blocks of cytoskeletal active matter and biomimetic nanomachines that recapitulate cellular motility, emergent pattern formation, and motor-driven transport. However, these canonical systems use MTs of fixed length and do not incorporate the natural ability of MTs to grow and regenerate. Here, we go beyond these limits by using dynamic self-amplifying branched MT networks. Driven by kinesin-1 and cytoplasmic dynein activity, surface-gliding branched MT bundles undergo swarming that yields large-scale collective MT architectures with several sought-after features. They are polar and orientationally aligned, dense, span millimeter scales, and persist over hours. We then show that these features enable molecular transport along the swarm at unprecedented capacities, with up to six million motor complexes walking in parallel across millimeter-scale distances over hours. Our results introduce a new regime in cytoskeletal active matter in which the interplay between motor-driven activity and filament generation via branching leads to emergent polar order in proliferating swarms. Such emergent polarity makes these swarms suitable for engineering scalable transport nanotechnologies and programmable soft materials.

In cells, cytoskeletal filaments such as microtubules are dissipative polymers that switch stochastically between growth and rapid collapse, a behaviour known as dynamic instability. This switching is coupled to nucleotide hydrolysis, so a filament's fate depends on the chemical state of its subunits and the free-monomer pool. Previously reported synthetic assemblies can be cycled between assembled and disassembled states, but the switch is typically set by the global fuel level rather than by a state stored within each monomer. Here we demonstrate a DNA/RNA hybrid polymer in which every monomer holds a one-bit internal state, assembly-competent or inactivated, flipped irreversibly by cleavage of an internal RNA linkage. The bit is written by two routes sharing the same transesterification chemistry: a slow spontaneous cleavage giving each monomer an intrinsic lifetime, and a fast, site-specific write by a programmable DNAzyme. Because inactivation is irreversible, sustained cycling requires continuous regeneration of active monomer, holding the system in a non-equilibrium steady state in which filaments undergo repeated depolymerization and rescue at frequencies near 0.2 (min)-1. We also find that the filaments form meshes auto-catalytically. Because each crosslink recruits filaments from the pool, crosslinking accelerates autocatalytically, driving a percolation transition to a system-spanning network that continuously remodels as its filaments turn over. Thus the timing of switching can be stored within individual monomers rather than imposed as a global threshold -providing a route to autonomously remodelling active materials.

While the physical aging of biomolecular condensates into macroscopic glasses is heavily linked to pathological disease states, the nanoscale topological rules governing this non-equilibrium relaxation remain elusive. Using heterotypic alpha-synuclein-Tau coacervates, we combine variable-stringency dissolution and FLIM-FRET to provide direct experimental mapping of the internal network reorganization over time. Rather than a passive, isotropic kinetic jamming event typical of classic glasses, we demonstrate that this physical aging is driven by continuous rheostatic network consolidation; a progressive, directed topological relaxation toward deeper free-energy minima powered by the cooperative spatial optimization of sticker motifs. We formalize these dynamics into a mesoscale series-resistance model derived from size-resolved kinetics, proving that thermodynamic quench depth dictates the initial network state while clustered sticker patterning introduces configurational frustration that kinetically stalls maturation to preserve liquidity. This multi-scale framework links sequence grammar to non-equilibrium transport laws, revealing how biomolecular assemblies navigate the boundary between physiological utility and pathological arrest.

Directed migration along chemical gradients controls immune surveillance, development, and cancer invasion. However, the same chemical cue can produce different responses depending on its concentration and whether cells move alone or in groups. For example, in steep gradients, isolated malignant lymphocyte cells migrate away from the chemoattractant source, whereas clusters of the same cells continue to migrate toward it. Here, combining computational modeling and experimental observations, we show that this reversal is governed by coupled mechanisms acting across molecular, cellular, and collective scales. At the single-cell level, our model predicts that receptor endocytosis generates a feedback that produces a nonmonotonic surface receptor density with increasing chemoattractant concentration. Above a critical concentration that depends on the cell's volume-to-sensing-area ratio, receptor depletion reverses cell polarity and drives chemorepulsion. However, in clusters, cell-cell contacts reduce the membrane area exposed to ligand, increasing the volume-to-sensing-area ratio, thus increasing the critical concentration and preserving chemotaxis. An agent-based model incorporating these mechanisms quantitatively reproduces the sign reversal of the migration index across gradient steepness and cluster size. We show that collective rearrangements further stabilize chemoattraction with exchanges between the cluster rim and core helping remove chemorepulsive cells from the leading edge, keeping their fraction below the threshold required to reverse cluster migration. The model further predicts, and experiments confirm, that increasing ambient ligand concentration while keeping the gradient fixed reduces cluster chemoattraction. Our results identify receptor trafficking, cell geometry, and cluster fluidity as physical determinants of collective directional decision-making, with implications for immune cell homing, tissue morphogenesis, and cancer dissemination.

Defining a body axis is a central aspect of animal morphogenesis. During regeneration from excised Hydra tissue pieces, the newly formed body axis typically preserves the orientation of the parent body axis and aligns with the inherited nematic organization of the supracellular actomyosin fibers. Here we show that this inherited orientation can be overridden by geometric confinement. Tissue spheroids confined in narrow cylindrical channels in a frustrating configuration, with the inherited axis initially perpendicular to the channel, regenerate with their body axis aligned along the channel. Using high-resolution live imaging we show that this reorientation is accompanied by remodeling of the nematic fiber organization. New fibers form parallel to the channel axis in the initially disordered closure regions, creating sharp domain boundaries with the inherited transverse fibers. These domain boundaries subsequently propagate, with perpendicular fibers dissolving and new fibers forming along the channel axis. The confined tissue behaves as a solid-like active nematic material, storing anisotropic strain over long timescales while allowing nematic reorganization relative to the material frame. Our results suggest that coupling between tissue strain and nematic alignment contributes to fiber reorientation and body-axis patterning, highlighting how external mechanical constraints can redirect the body axis during morphogenesis.

During gastrulation, embryonic epithelia undergo large-scale remodelling to internalise the mesoderm. Whether the cellular mechanisms underlying these tissue deformations are conserved across species remains unclear. Using quantitative cell-shape embedding, we compare cellular behaviours underlying gastrulation in two insects. We show that while Drosophila mesoderm cells follow a coordinated shape change sequence during gastrulation, mesoderm cells in the beetle Tribolium display heterogeneous shapes with no clear trajectory. This heterogeneity arises from two distinct internalisation modes: canonical apical constriction-driven tissue invagination, and early internalisation through out-of-plane cell divisions. Interpretable machine learning together with in vivo perturbations identify nuclear crowding as a key predictor of out-of-plane divisions and show that, in both species, proliferation slows tissue folding while promoting individual cell internalisation. Our study showcases morphospace analysis as a powerful tool for dissecting the cellular basis of tissue morphogenesis and reveals a conserved antagonistic relationship between cell divisions and tissue folding during gastrulation.

Chromatin is an actively remodeled polymeric system whose organization emerges from the interplay of equilibrium interactions and ATP-dependent processes. Recent in vitro experiments show that nucleosome spacing and ATP-dependent remodeler activity significantly influence chromatin condensate properties. Here, guided by these observations, we develop a hierarchy of coarse-grained models that systematically dissect the roles of nucleosome spacing, remodeler-mediated binding-unbinding kinetics, and active force generation in governing condensate dynamics. We demonstrate that nucleosome spacing heterogeneity is a key determinant of condensate material properties. Condensates formed from regularly spaced fibers exhibit enhanced internal mixing, whereas those assembled from disordered spacing develop pronounced structural correlations, increased entanglement, and suppressed internal dynamics. Incorporating remodeler-like binding-unbinding nonequilibrium kinetics drives local structural reorganization, leading to condensate swelling and a substantial acceleration of internal relaxation. In condensates of heterogeneous fibers, contrasts in spacing and activity robustly drive spatial segregation, giving rise to stable core-shell architectures. Strikingly, when dipolar forces are coupled to hydrodynamic interactions, serving as a minimal representation of active nucleosome translocation, condensates exhibit enhanced center-of-mass motion. Together, our results establish a predictive coarse-grained framework that quantitatively links structural heterogeneity and active processes to emergent chromatin-like condensate organization, mechanics, and transport.

Developmental patterns can scale with size during growth, a phenomenon commonly attributed to morphogen scaling. Although patterning is orchestrated by gene regulatory networks (GRNs) activated by morphogens, how GRN dynamics interact with growth is not understood. We present a theoretical framework that integrates morphogen signalling, GRN dynamics, and tissue growth. We show that pattern scaling emerges from the interplay of GRN dynamics and growth, even in the absence of morphogen scaling. This relies on memory effects encoded in the GRNs, providing a cell-autonomous route to global scaling, and offering a general mechanism for size-invariant patterning beyond morphogen-based models.

Electrical signaling in biological systems is generally understood through the lens of single-channel biophysics, yet whether ensembles of ion channels can undergo cooperative opening and closing remains unclear. Here, we show that ensembles of voltage-gated ion channels can undergo bioelectrical order-disorder phase transitions driven by feedback between channel currents and local membrane voltage. When channels open, they carry ion-selective current that redistributes ions near the membrane and perturbs the transmembrane potential, thereby biasing the gating of nearby channels. This emergent nonequilibrium coupling generates a bona fide phase transition in ion channel ensembles. Finite-size analyses of the open-channel fraction, its fluctuations, and the distribution of collective channel states yield a voltage-temperature phase diagram with a first-order line separating collectively open and closed states and terminating at a critical point. The critical temperature is governed by a dimensionless conductance ratio set by ion transport, channel density, and confinement geometry. Applying this framework to measurements from the squid giant axon, the axon initial segment, and the nodes of Ranvier suggests that collective activation may be favored by high sodium-channel densities in large-diameter nerves, whereas the lower densities typical of potassium channels place them in an independent-gating regime.

Molecular information is vital for imaging technology. Optical imaging acquires molecular specificity almost exclusively via labeling strategy, which is fundamentally constrained by limited multiplexing capacity, high running costs, and experimental complexity. Conversely, label-free optical imaging offers substantial technical simplicity but is believed to have little true molecular specificity. Contrary to common belief, here we introduce super-multiplex optical imaging without labeling. By systematically studying paired vibrational spectroscopic imaging and mass spectrometry imaging, we discovered a surprisingly strong (more than 0.9) correlation between their latent space representations, supported by both experiments and theory. This insight prompts us to build supervised learning models to successfully predict spatial distribution of 100 molecular species directly from label-free vibrational images across diverse tissue systems. We developed this technology, named Prediction through Learning with AdvaNced Chemical Kaleidoscope (PLANCK), and demonstrated it with both infrared-based vibrational imaging of organ-scale tissues and Raman-based vibrational imaging of live tissues. Powered by AI, PLANCK decodes the exquisitely rich but otherwise hidden vibrational information into a surprisingly large number of ([≥]100) specific molecular species, providing a cost-effective and scalable solution for basic research and translation, including applications in live imaging.

Plant morphogenesis emerges through the coordinated regulation of cell growth and mechanical interactions across multiple spatial scales. A central role in this process is played by cortical microtubule (MT) arrays, which guide cellulose deposition and thereby regulate anisotropic cell expansion. Here, we develop a coupled multiscale computational framework integrating a dynamic vertex model of tissue mechanics with a stochastic model of cortical MT dynamics. Within this framework, MT organization regulates anisotropic cell-wall stiffness, while evolving cell geometry feeds back to influence MT alignment through bidirectional mechanochemical coupling. Simulations show that distinct regimes of MT self-organization generate qualitatively different tissue growth behaviors, ranging from isotropic expansion to strongly anisotropic elongation. Together, our results demonstrate that stochastic a complex coupling of MT self-organization with cell geometry and tissue mechanics is sufficient to generate emergent tissue-scale growth anisotropy, establishing a minimal multiscale framework linking cytoskeletal dynamics to plant tissue morphogenesis.

Precise, non-invasive manipulation of individual living cells remains a central challenge in biomedical science, with far-reaching implications for single-cell analysis, tissue engineering, and the study of cell-cell interactions. Here, we report the first demonstration of single-cell control using bulk acoustic standing-wave acoustofluidics with closed-loop feedback. We introduce VeLO (Vector-based Local Optimization), a model-free, reinforcement learning-inspired algorithm that enables programmable two-dimensional manipulation of individual cells using a single piezoelectric transducer. Without prior calibration or physical modeling, VeLO learns system dynamics online from acoustically induced cell displacements and automatically adapts to nonlinear, time-varying conditions. We achieve robust control across multiple cell types (DU-145, Jurkat, K-562) and independent manipulation of multiple cells, including controlled cell-cell contact. By combining simplicity of hardware with autonomous, adaptive control, this approach establishes multimodal acoustofluidics as a versatile tool for label-free, high-precision single-cell manipulation.

The nanoscale organization of cell-adhesive ligands is increasingly recognized as a determinant of cell behavior, yet whether it directly regulates cellular metabolism remains unclear. Here we show that supramolecular clustering of integrin-binding ligands regulates mitochondrial respiratory capacity through integrin-mediated mechanotransduction. Supramolecular ligand clustering induces integrin redistribution and cytoskeletal remodeling, leading to mitochondrial reorganization and a selective constraint on oxidative phosphorylation. This respiratory limitation functionally constrains tumor cell migration and invasion and cannot be overcome by restoring cytoskeletal contractility, whereas replenishing mitochondrial metabolic substrates effectively rescues motility. In a HeLa xenograft model, the integrin-binding supramolecular system suppresses tumor growth and reduces extracellular matrix deposition. These findings identify mitochondrial respiratory capacity as a critical downstream effector of integrin mechanosignaling and establish extracellular ligand organization as a previously unrecognized driver of mechanically encoded metabolic regulation.

There are several ways in which the nanoscale array of cellulose fibrils in one layer of a plant cell wall can rearrange to permit the cell wall to expand under external uniaxial tension or, in the case of primary cell-walls, the biaxial turgor pressure that drives growth. Here, seven such deformation modes were identified and their scale-independent geometry was described: fibril rotation, regular shear, interdigitated sliding, fibril stretching, fibril respacing and the formation and straightening of waves. The distinction between regular shear and interdigitated sliding was introduced to capture a continuous range of sliding modes at fibril interfaces. Combinations of these nanoscale deformations were examined to find out how their relative magnitude must vary to satisfy cell-scale geometric constraints. When the cellulose fibrils were transversely oriented, respacing, wave formation or both were needed for elongation. When the tissue restrained twist to zero, the deformation modes became co-ordinated, readjusting as the cellulose orientation became more axial during elongation. Regular shear, possibly facilitated by expansin activity, could then control the width of the elongating cell-wall. Each deformation mode fortuitously contributed most elongation at the microfibril orientation where it was most efficiently driven by the local force vector.

How embryos of different sizes generate reproducible body plans remains a central question in developmental biology. Do larger embryos contain more cells, or preserve conserved organizational principles that ensure robust tissue patterning independent of scale? Here, we address this question through whole-embryo quantitative mapping of cell number, tissue allocation, and spatial organization during early development in Xenopus. Using optimized in-toto 3D imaging, tissue clearing, and deep-learning for nuclei segmentation, we quantified cell numbers and reconstructed the spatial distribution of cells in early embryonic stages. Although X. laevis embryos exhibited substantially larger embryo volumes and higher total cell numbers than X. tropicalis, the proportional allocation of cells among ectoderm, mesoderm, and endoderm remained highly conserved between species. In addition, quantitative analysis of local cellular neighborhoods revealed striking conservation of spatial order, packing geometry, and large-scale tissue architecture despite major differences in embryo size and cellular density. Together, these findings demonstrate that early vertebrate embryos follow shared quantitative design principles in which embryonic scaling occurs without disruption of the underlying cellular blueprint of the body plan. Our study establishes a quantitative framework for comparing embryonic architecture across species and provides evidence that developmental organization is governed by conserved scale-invariant topological principles.

Chemotaxis drives cell migration in processes ranging from wound healing to embryonic development and cancer metastasis, yet its quantitative understanding remains limited because responding cells change and degrade attractant gradients, and existing datasets are too small and imprecise to capture stochastic behaviour. We present ChemoTrack, a publicly accessible resource comprising 2 million measurements from 500,000 migration tracks, in which the chemoattractant gradient and concentration experienced by every cell at the time of observation are precisely determined. The dataset includes microscopy images and trajectories spanning a full range of biologically relevant chemotactic conditions. Analysis shows that cells steer according to absolute differences in active receptor number, not fractional receptor occupancy, and maximal chemotaxis is not predicted by half-maximal receptor occupancy. By combining scale, precision and accessibility, ChemoTrack shifts quantitative description of eukaryotic chemotaxis from experimental conditions to the instantaneous chemical signal experienced by individual cells, enabling future mathematical and mechanistic analyses.

Synthetic gene circuits provide experimentally tractable systems for dissecting how genetic feedback and diffusible signals generate multicellular patterns. However, building multi-component circuits whose behavior can be quantitatively linked to module-level measurements, diffusion, and spatial boundary conditions remains challenging. Here, we designed and engineered a bacterial patterning system in which positive feedback, delayed negative feedback, and two orthogonal quorum-sensing signals are integrated in Escherichia coli. We first implemented and characterized the feedback modules separately, measured the effective diffusion of the signals in the experimental setup, and used these data to parameterize a mathematical model. In quasi-2D bacterial lawns, the complete circuit generated self-organized spatiotemporal dynamics consisting of an sfGFP activation front followed by successive mCherry propagating pulses/traveling waves. Model-guided perturbations showed that lawn size, lawn position relative to the domain boundary, and signal degradation modulate the timing, amplitude, wavelength, and directionality of these patterns. Our work establishes a modular synthetic multicellular reaction-diffusion system in which circuit architecture, signal diffusion, and boundary-mediated signal exchange can be experimentally connected to emergent patterning dynamics.

Biomolecular condensates are dynamic assemblies whose functions depend on continuous exchange of molecular components with the surrounding environment. While scaffold molecules drive phase separation and condensate architecture, many functional components are clients that are recruited through interactions with the scaffold-rich environment. Despite their prevalence, how client-scaffold interactions shape client exchange dynamics remains poorly understood. Here, we develop a reaction-diffusion model for client exchange in scaffold-driven condensates, in which clients switch between a scaffold-bound state and an unbound state. Bound clients exchange through scaffold-mediated transport, whereas unbound clients diffuse through the pore space of the condensate. Using the fluorescence recovery of fully photobleached condensates as a measure of client exchange, we compare transport through these two pathways with bound-unbound conversion and identify three limiting regimes. In the slow-conversion regime, bound and unbound clients recover through distinct scaffold- and pore-mediated pathways. In the intermediate-conversion regime, recovery of bound clients becomes limited by client unbinding. In the fast-conversion regime, local equilibrium between bound and unbound clients produces an effective single-state recovery. We further propose a unifying description that connects these regimes and quantitatively captures the apparent recovery timescales extracted from numerical simulations across condensate sizes. Our results provide a framework for interpreting component-specific exchange dynamics, and highlight client size, client-scaffold binding, and condensate porosity as key regulators of client turnover in multicomponent condensates.

Biomolecular condensates are dynamic, membrane-free compartments that continuously exchange molecules with their surroundings. The dwell time, defined as the time a molecule remains inside a condensate between entry and exit, determines how extensively the molecule can explore the dense phase and encounter potential binding partners or reaction sites, thereby modulating condensate function. Motivated by our single-molecule measurements of RNA dwell times, we developed an analytical theory to understand dwell-time distributions in biomolecular condensates. Our theory predicts that the dwell-time distributions generally exhibit an early-time power-law regime followed by a late-time exponential tail. The form of the distribution encodes the rate-limiting mechanism of molecular escape: dense-phase diffusion-limited transport feature a -1.5 power law with an exponential tail set by a diffusion timescale, whereas interfacial barrier-crossing-limited transport feature a -0.5 power law with a decay governed by a barrier-crossing timescale. These distinct signatures provide a direct readout of the physical processes that control molecular retention in condensates, with implications for both natural and synthetic condensates.

Cell extrusion is a fundamental process in tissue homeostasis, morphogenesis, and cancer progression, facilitating the removal of cells either alive or through apoptosis. While biochemical signaling pathways are known to regulate extrusion, recent advances have underscored the importance of mechanical forces in this process. Here, using optogenetic control of RhoA activation in epithelial monolayers combined with Bayesian Inversion Stress Microscopy (BISM) and three-dimensional cell-based modeling, we uncover a counterintuitive mechanism whereby elevated tension, instead of stabilizing the monolayer, actively drives extrusion in highly contractile cells. We show that local RhoA activation enhances myosin II-dependent contractility and F-actin reorganization, which promotes cell stiffening, resulting in localized tension buildup. The ensuing tensile stress amplifies vertical mechanical fluctuations, which in turn trigger cell extrusion. Remarkably, these tension-induced extrusions occur both apically and basally. Furthermore, our findings show that RhoA-mediated contractility is not merely an effector of extrusion but also an active promoter of basal extrusion, independently of caspase activation. Our study demonstrates that tensile stress can directly initiate extrusion events and bias their outcome toward apical or basal fates. By identifying tension as a driver rather than a suppressor of extrusion, this work revises current models of epithelial homeostasis and highlights mechanical control as a targetable axis in disease and regeneration.